Many Gram-negative bacteria interact with hosts using surface-exposed lipoproteins (SELs), and SELs have proven to be excellent vaccine and immune system targets. Nevertheless, the major pathway by which SELs are exported to surfaces of Gram-negative cells is unknown. The overall goal of this project is to understand how SELs are transported to the surfaces of Gram- negative cells. This will be accomplished using model SELs and genetics in E. coli to identify genes that encode the components of the E. coli SEL export machinery. To this end, a combination of directed and random mutagenesis approaches will be employed. Model SELs will also be studied to identify features that direct these lipoproteins to be exported to the cell surface. Truncations and transposon mutagenesis of several different model SELs will be used to identify the portions of these SELs that are required for their export to the cell surface. Following this, bioinformatics approaches will be used to compare the portions of different SELs that are required for their export in an attempt to identify a SEL surface-exposure motif. If a motif is identified, its validity will be experimentally tested. By understanding the mechanism by which SELs are exported to Gram-negative cell surfaces, it may become possible to prevent them from reaching the cell surface in Gram-negative cells that utilize SELs as virulence factors. In addition, by elucidating an SEL surface-exposure motif, it may become possible to accurately predict which putative lipoproteins could be potential surface-exposed vaccine targets and which reside in the periplasm. PUBLIC HEALTH RELEVANCE: Surface-exposed lipoproteins (SELs) are used by many Gram-negative bacterial pathogens to cause disease, and are excellent vaccine targets. However, it is not understood how most SELs arrive on the surfaces of these organisms. By studying the mechanisms that deliver SELs to the surface of Gram- negative cells, it may become possible to prevent them from reaching this location, as well as to accurately predict which Gram-negative lipoproteins should and should not be targeted by vaccines.